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Predictions 2018: Random Thoughts on AI, DevOps and Other Topics

In doing this series, we’re reflecting the knowledge and depth of field that our readers have in sectors all over the IT business. These are your stories, not ours.

If you’re a regular eWEEK reader, you’ll know that we’ve been running a long series of “Predictions 2018” articles all month, and we enjoy doing them. All of us like to find out what’s coming from the future via experts whose perspectives are undoubtedly better than our own.

In doing this series, we’re reflecting the knowledge and depth of field that our readers have in sectors all over the IT business. eWEEK’s been around a long time—at first as PC Week from 1983 to 2000—and, like things you gather for your home over the years, we’ve earned a lot of loyal readers along the way. To all of you, we say: “Thank you, and continue to help us stay ahead of the IT curve, so we can package your knowledge and publish this information for you every day.”

Frankly, it’s also nice that all we really need to do it edit these predictions, write a lead-in, whip them into a coherent style and publish them for you. These are your stories, not ours.

With that, today we’re publishing a potpourri--a series of random prognostications—about trendy and topical IT sectors. It’s sort of like shopping at Marshall’s, Home Goods, Tuesday Morning or a second-hand store; you never know what you’re going to find. We might come up with a few more before the end of the year, too.

Further reading

Here are those random predictions. Enjoy, and have great holidays and a wonderful new year!

Nara Rajagopalan, CEO, Accelerite: AI isn’t just a hype; thinking machines WILL rule our lives (perhaps not literally).“My school-going daughter is playing with Tensorflow to see if she can generate harmonies for any given song for her choir. She doesn’t know the math behind the learning algorithms, but things are getting easy enough for most people who can write some code to explore machine learning. While the basic math behind AI has been well understood for years now, the cost of compute an its availability along with the tooling around it is moving at a fast pace to democratize AI.

"Several companies including us are exploring if we can convert a Q&A worksheet of what one wants to predict into learning programs. The job of assembling meaningful learning data sets, seeing the accuracy of predictions, constantly tuning the algorithms, even picking different ML models to improve your predictions – all of this is getting easier by the day. Not only are the machines learning, but they are picking and choosing among various learning algorithms to see which predicts the future better. Scary--and you thought Elon Musk is nuts to think machines will rule the world!”

Daniel Saks, CEO and co-founder of AppDirect: 2018 marks the beginning of the digital economy.“We’re connecting all devices online and in the cloud over the next 10 years. In 2018, we will see more connected machines than ever before. This will have a massive impact on manufacturers themselves as they now have the opportunity to remain competitive. They are essentially supporting the creation of a digital supply chain, which enables companies to run their business in the cloud and ultimately meet consumers’ demands. The combination of Infrastructure-as-a-Service, Software-as-a-Service, and distribution technologies is what makes this possible.

“For example, AWS reduced the cost of computing technology and SaaS companies have reduced costs for general business functions such as payroll, inventory, finances, etc., and now it’s cheaper than ever for distribution. Just look at how Amazon Prime drastically reduced the cost of shipping and delivery, which ultimately means new opportunities for logistics companies. The companies that embrace digital practices early on will be able to transform faster than others, and those that fuse traditional with digital practices will be the ones that ultimately thrive in this digital revolution.”

The specialized bare metal cloud revolution will start at the edge. “Specialized bare metal instances will become available at the edge where ML/AI/and low latency processing are required. The major cloud providers will enable additional edge optimized capabilities that will augment core data centers.”

Edge computing will create virtual shot on goal. “Edge computing will enable Sports Entertainment Companies to create AR/VR experiences of plays and scores from various field/court. Additionally, it will be possible to watch a game or match in “the best seat in the house” from the best seat in your house via this capability.”

“As the need for optimized speed and bringing down Mean Time to Repair (MTTR) continues to grow, companies are looking for ways to become better at observability and getting a pulse on what’s happening to their system without having to make a risky move. Given this, more companies will look to bridge the gap and meet in the middle between traditional ITSM and DevOps.”

“We will see a blending of IT roles within Dev and Ops, creating more of an “engineer” position. For example, traditional roles such as Quality Assurance (QA), Sec, Ops and Database Administrators (DBAs) will blend together into engineering teams that are more product-focused.”

“With continuous delivery practices continuing to grow, we expect to see more engineering teams – regardless of responsibilities – want to know what’s going on within their delivery efforts through insights and analysis. Today's engineering teams demand that they know about problems sooner and sooner in the systems development life cycle (SDLC). If it's actionable, they want to be alerted well before it makes it to the end of the delivery pipeline and in to production.”

“There will be a shift in terms of how people think of DevOps itself. DevOps has generally meant the process of speeding up the delivery of software, but I think more organizations are realizing that it’s all about delivering the value of your product/service to the end user. It’s as simple as that.”

Ted Dunning, Chief Application Architect, MapR Technologies: DataOps emerges as the key organizational approach to drive agility.“We see a trend toward embedding data scientists and data-focused developers into otherwise traditional DevOps teams to form a DataOps team. Better communication, focus and goal orientation by cross-skilled teams results (importantly) in faster time to value and better agility. Organizing work in a DataOps style improves the ability for timely and appropriate responses to changing conditions. Better flexibility and efficiency at the human level helps take full advantage of new technologies and architectures.”

LogicMonitor:“Our research found that in 2017, 37 percent of all IT workloads continue to run predominately on-premises, with 31 percent in the public cloud. However, over the next two years, the percentage of premises-based workloads will drop to 27 and workloads running in the public cloud will grow to 41 percent with the balance running on private or hybrid clouds. Key drivers of this transition: 63 percent cited digital transformation followed closely by IT agility (62 percent) and DevOps (58 percent). This changes dramatically by 2020 when AI and machine learning takes the lead, followed by IoT.

Alexa will make the leap to the enterprise. “Most people think of Alexa as a home device, but in 2018, people will begin to use it for administrative tasks at work. Its traction will follow the paradigm the iPhone and Google Drive set for business adoption. Over the next couple of years, two beachheads will emerge: the C-suite (commanding calendars, ordering lunch, and paging employees) and meeting rooms (pulling a presentation onto the big screen, dialing out to remote employees).”

The term AI is overused; true AI will begin to be implemented In 2018. “The worst-kept secret around AI is that a very small handful of companies (like Google and Facebook) are actually doing it – everyone else is mostly just able to use statistics. In 2018, we’ll see companies begin to pilot real AI in targeted ways, like understanding patterns in shipping and manufacturing, making health diagnoses or applying basic machine learning to big data.”

Automated compliance assessment and remediation becomes vital to DevOps maturity. “The continued growth of infrastructure automation at scale means compliance will become even more vital, and more complicated in 2018. Major security breaches in 2017 heightened business concerns about security; the adoption of distributed applications has placed control ever further out of IT’s reach; and new regulations like GDPR have put demands on organizations globally. Companies will reach a turning point in 2018, seeking out automated compliance assessment and remediation tools that will help them keep up with these changes by treating compliance as code. The recent Forrester Wave: Configuration Management for Infrastructure Automation, Q4 2017 describes the rising significance of compliance.”

Containerization flexes its maturity muscles. “Every year since 2014 has been touted as the ‘year of containerization,’ and 2018 is no different. This year we will see increased vendor specialization in key areas such as security, networking and storage, and a flattening of the competitive landscape for critical enabling technologies such as orchestration and scheduling. We will also see new tools enabling application automation, and the lowering of the bar for multi-cloud and multi-platform application development and deployment among the enterprise: a hybrid reality which is going to be around for some time.”

AI takes a more prominent role in data center operations. “Recent innovations in data center monitoring, management and automation have brought enterprises a long way towards application- and infrastructure-focused operational excellence. Still, no matter how advanced the tools, the people, along with the delays and errors from manual processes, still limit performance in IT infrastructure[WC1] . The next wave of data center quality and competitive advantage will be driven by elimination of the delays and the errors introduced by human intervention. Applying artificial intelligence to data center operations will separate data center leaders from those who simply survive and these advances will drive the next cycle of business innovation.”

IoT and the data center. “IoT is already driving massive changes in how data centers are designed, provisioned, monitored, and managed, and the impact is only just starting to be felt. 2018 will see colocation providers and their enterprise customers leveraging the capabilities and insights from the massive influx of data to establish new levels of insight, performance, and efficiency. The success in developing winning strategies for how businesses will assess and deploy management and analytics to run more efficient and higher performing solutions will help define the industy leaders in future generations of datacenter technology.”

Gary Tyreman, CEO, Univa: HPC begins a major move to hybrid cloud. “For years, analysts have predicted the migration of high-performance computing to the cloud, but adoption has been slow. Aside from oft-cited concerns like bandwidth, latency, and compliance issues, there are other barriers including complexity, software licensing terms, and concerns about proprietary lock-in. Perhaps the biggest barrier is related to cost. Sustained utilization in well-run HPC centers can exceed 90 percent leading to rock bottom per core-hour costs that make cloud look expensive by comparison.

"Despite this, HPC users have an insatiable appetite for computing power. As we stand on the cusp of a new year, these barriers are now falling away. Cloud providers offer HPC optimized systems, applications are increasingly open-source or have cloud-friendly licenses, and technologies like containers ensure portability. It is now easy to tap cloud-based compute cycles opportunistically, economically, and seamlessly. The stars have aligned, and for HPC practitioners, hybrid cloud will become essential to ensuring competitiveness.”

Rob Lalonde, General Manager, Univa: Container orchestration getting to scale. “While Docker and containers are all the rage, getting to scale is hard. Modern “born-in-the-cloud” applications benefit from container orchestration, but these applications are still the minority. Organizations have sunk investments in non-containerized applications including databases, app servers, and big data environments. Re-engineering applications to run on Kubernetes is like trying to iron your shirt while you’re wearing it. It’s hard, and you’re likely to get burned if you try.

“What’s exciting is that new technologies are now making it possible to run existing workloads on Kubernetes, without the need to re-write or significantly alter applications. For the first time, cloud-native apps, traditional non-containerized apps, and even big data and HPC workloads can run on a shared Kubernetes substrate. These innovations allowing different types of applications to share infrastructure will help us see container orchestration get to scale this year.”

Dean Hager, CEO of Jamf: In 2018, we’ll see the rise of machine learning and augmented reality.“Machine learning is already present with Apple to an extent, as Siri provides suggestions based on your search history, but the possibilities of machine learning could be virtually endless in the future by leveraging the entire Apple ecosystem. Augmented reality (AR) is going to be monumental in education and healthcare. In education, AR will bring students to another place, culture, time and allow them a learning experience unlike any other. Real “field trips” done in real time, right from the classroom. And, as most of us know, a hospital stay is not very pleasant. While iPad at the patient bedside is drastically improving the healthcare experience, imagine a future where a patient can virtually checkout of their room and take a break from the stress of treatment.”

Multicloud continues fueling complexity. “Customers will continue to build out their multicloud strategies in 2018, navigating and leveraging the many clouds and many vendors that make up a multicloud environment. While a multicloud approach can deliver tremendous benefits, it can also create complexity, exposing a gap between the business need for digitization and what IT can reliably and confidently support. This growing complexity has less to do with the value of the individual services and more to do with how to efficiently and effectively manage, secure, deliver, and gain insights across all the cloud services customers use. However, there is little to no connective tissue between these vendor-specific clouds; each having their own tools, APIs, configuration requirements, SLAs (service-level agreements), analytics, and more. As we move into 2018, taking this complexity into account will be critical to connecting the dots when it comes to customers’ cloud strategies and doing more with cloud.

Enterprises will need to harmonize their cloud environments. “Customers tell us they want a common framework that ideally mirrors on and off prem; a “golden thread” to effectively, plan, build, and securely manage multicloud environments. Organizations must strike the right balance between control and innovation across their on- and off-premises environments and multiple clouds from various providers. In 2018, look for enterprises to put more resources into building cloud management frameworks and tools across on-prem and cloud, and treat those environments as a single system. IT organizations will focus on building IT governance and infrastructure that enables the ability to develop, run, secure and monitor workloads across multiple clouds, optimizing existing investments, while planning cloud migration at their own pace and avoiding lock-in.”